An experimental evaluation of computer graphics imagery
ACM Transactions on Graphics (TOG)
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Transferring color to greyscale images
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
IEEE Computer Graphics and Applications
Distinguishing photographs and graphics on the World Wide Web
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
Measuring the perceived visual realism of images
Measuring the perceived visual realism of images
Example-Based Color Stylization of Images
ACM Transactions on Applied Perception (TAP)
The Design of High-Level Features for Photo Quality Assessment
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
LabelMe: A Database and Web-Based Tool for Image Annotation
International Journal of Computer Vision
Data-driven image color theme enhancement
ACM SIGGRAPH Asia 2010 papers
Scene illumination as an indicator of image manipulation
IH'10 Proceedings of the 12th international conference on Information hiding
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
CG2Real: Improving the Realism of Computer Generated Images Using a Large Collection of Photographs
IEEE Transactions on Visualization and Computer Graphics
Learning photographic global tonal adjustment with a database of input/output image pairs
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
How realistic is photorealistic?
IEEE Transactions on Signal Processing
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Photorealism has been one of the essential elements in producing computer generated imagery. The state-of-the-art techniques employ various rendering algorithms to simulate physically accurate light transport for generating a photorealistic appearance of scene. However, they require a labor-intensive tone mapping and color tunes by an experienced artist. In this paper, we propose an automatic photorealism enhancement algorithm by manipulating the color distribution of graphics so to match with that of real photographs. Our hypothesis is that photorealism is highly correlated with the frequency of color occurrence in real photographs; more often we observe more realistic we believe. Based on this hypothesis, we find principal color components by following two steps. First, we extract the most representative features from the color distribution of photographs. Then, we obtain the coefficients of the most distinguishable principal axis to separate the features of photographs and those of graphics. The distribution of these coefficients constructs the color distribution of graphics and real photographs, respectively. Then, we modify the statistical characteristics (orientation, variation and the mean of color distribution) of graphics according to that of photographs. Experiments and user study have confirmed the effectiveness of proposed method.